class_docstr: LightningMultiDataLoader class is used by DatasetLoader class to load multiple
  datasets and more granular. This class overrides some functions from MultiDataLoader
  to make them lightning trainer compatible
code: def has_len(self):
      for loader in self.loaders.values():
          if not hasattr(loader, "dataset"):
              continue
          dataset_instance = loader.dataset
          if not hasattr(dataset_instance, "__len__"):
              return False
      return True
  
file_path: mmf/mmf/datasets/lightning_multi_dataset_loader.py
imports: import math
  from typing import Dict
  from mmf.datasets import iteration_strategies
  from mmf.datasets.multi_dataset_loader import MultiDataLoader
  from torch.utils.data import DataLoader
label_desc: Use image node_id 2 for calling the LightningMultiDataLoader obj's underlying member method code with example usage: obj.has_len() and returns: True, False